Financial services companies want to grow revenue, reduce cost and deepen customer relationships. They want to innovate quickly at a reasonable cost and manage the associated risk. They ultimately want to get customers what they want or need as quickly as possible with minimal effort.
autologic powers the tools to help employees or customers make decisions they would otherwise make manually or make at all.
Building tools that aid decision making requires logic, but the challenge is the people who understand the customer or company problem on which that logic is based aren’t usually software engineers. They are analysts, product managers, marketing managers, designers, ux designers, product owners and the like.
autologic lets these non-technical people build the complex calculations & logic required to power decision tools or processes. It frees your software engineers from having to code and maintain complex logic. It gives your risk people visibility and confidence the logic is and remains accurate overtime
autologic has built a web based interface to allow non-technical people to build complex calculations and logic and then presents a set of APIs that enable engineers to hook up that logic to the tool or process where the logic is needed.
If you can use excel you can use autologic to build your logic.
autologic can be the logic behind virtually any tool or process but here are some specific examples we have seen already
Logic is the combination of 4 main components
autologic provides an interface to create these four components, built around whatever data model you need to represent the decision you need made. It uses a ‘schemaless’ design that means if you can imagine it, you can build it. It is not pre-built around specific use cases or industries.
You start by creating the Inputs and Outputs Schemas, placeholders for the questions you need to ask and the answers you want to return. autologic supports a wide range of datatypes for both Inputs and Outputs
You then add Resources, raw data that your rules will lookup to help build the Outputs
Finally you create Rules that define;
Much like excel you can daisy chain Rules to create whatever level of complexity your logic requires.
autologic includes a test framework built right into the web based editor which means you can test your logic as you build and you can have a set of test cases that mean when you modify your logic in one area you don’t accidentally break the logic in another area.
QA and Risk people love autologic as they can see and run test coverage over a schema, product, provider or entire instance quickly and easily.
autologic is designed to power OTHER things like interfaces or systems that are the tool or process. It is a fully hosted solution and deployed by way of integration via API from these tools or processes that need the logic. Engineers are required to send autologic the Inputs and handle the Outputs is generates, all via API
Once deployed any changes to your Rules or Resources can be done on the fly without any need to engage an engineer. Typically this will represent over 95% of the changes you want to make day to day.
If you want to extend your Inputs or Outputs you may need an engineer to ensure the new data is sent and/or received in the tool or process that is using the logic
autologic is hosted on Google Cloud under a single tenancy model with dedicated project folders for each enterprise customer.
This single tenant with multiple folders approach helps autologic to isolate and apply Organizational policies for individual tenants and yet manage them centrally.
autologic has undergone numerous 3rd party security audits over the last 5 years. Details are available on request
Autologic uses Google Security Command Center to manage vulnerability assessment scanning that can automatically detect highest severity vulnerabilities and misconfigurations for Google Cloud Assets. Autologic also leverages Web Security scanners for identifying any security risks in OWASP Top Ten. Cloud Armour is enabled for protecting applications and websites against DDOS and web attacks.
autologic houses only your logic, not your customer data. You may send us customer data (typically not personally identifiable data as this isn’t usually needed for logic). Either way when you send us Inputs these are used to generate Outputs at that moment in time and are then discarded once the Outputs are returned.
autologic was spun out of UNO Home Loans after 5 years and millions of dollars of investment. It powers all logic inside of UNO and has run without interruption over that time other than an AWS outage (where it was previously hosted)
autologic has an architecture that sees the heaviest part of the process run entirely in memory. This means that even for very intensive logic it is highly performant. We have seen numerous instances where it is powering interfaces in real time as customers lose focus on fields new data is sent and calculations are returned. This happens in fractions of a second
autologic can also be set to match the location of users in terms of hosting location to reduce latency
The in-memory architecture of autologic provides for a massive amount of scale already however the real power behind supporting thousands or millions of customers is in the architecture at Google Cloud which deploys a range of measures to respond in near real time to spikes in usage from our customers
autologic uses Google managed Kubernetes for compute and Cloud SQL as a backend store. Both these platforms can scale independently of each other based on defined metrics. Additionally using these Google managed services could allow Autologic to scale into new geographies or locations which are closer to the customers.
autologic has a mission to replace custom code as the method of building the complex logic that powers your tools and processes. Our commercial model is therefore designed to always be cheaper than coding, hosting and maintaining your own solution.
The commercial model is simply the Google Cloud costs directly attributable to your autologic instance plus 25% (plus any applicable local taxes). For an instance that is in pilot this might be a few hundred dollars a month. For an instance that is live with thousands or 10s of thousands of users this might be in the thousands of dollars a month. For deployments into very large customer bases it’s going to be in the hundreds of thousands a month, directly related to your resource usage.
autologic is already highly efficient however as we continue to invest in improving the code and architecture and as cloud compute costs come down over time generally, these will all lead to a reduction in your underlying resource cost and thus bill.
You can optionally buy support services that will 100% enable you to move faster and get more out of autologic but there is a wide range of materials to enable you to self-serve if you choose not to do so.
The best way to get started is to commit to a 3 or 6 month pilot that includes both a dedicated instance and a bunch of consultancy and support to upskill your non-technical people to build the complex logic to power your first tool or process and to support the integration and deployment of this via your engineering team. At only $17k USD for a 6 month pilot with no other costs it is the best way to get moving and provide immediate benefit around a specific use case whilst educating your organization on autologic. We typically see customers planning their 2nd and 3rd use case while still building their first